Semantic matching. While product search leverages a wide range of ranking features [1]}, features that do not rely on popularity or past interaction behavior, are deemed to be important as well. Semantic matching is one of the most important techniques to improve the ranking in product search [2]}, [1]}.
Several semantic matching methods have already been applied in the area of product search to generate latent representations for queries and product descriptions [4]}, [5]}, [1]}. Surprisingly, despite recent advances in supervised learning to match methods (see Section  for an overview), relatively little is known about the performance of these methods in the setting of product search.
